The SVD Beamformer: Physical Principles and Application to Ultrafast Adaptive Ultrasound

Hanna Bendjador, Thomas Deffieux, Mickael Tanter
2020 IEEE Transactions on Medical Imaging  
A shift of paradigm is currently underway in biomedical ultrasound thanks to plane or diverging waves coherent compounding for faster imaging. One remaining challenge consists in handling phase and amplitude aberrations induced during the ultrasonic propagation through complex layers. Unlike conventional line-per-line imaging, ultrafast ultrasound provides backscattering information from the whole imaged area for each transmission. Here, we take benefit from this feature and propose an
more » ... propose an efficient approach to perform fast aberration correction. Our method is based on the Singular Value Decomposition (SVD) of an ultrafast compound matrix containing backscattered data for several plane wave transmissions. First, we explain the physical signification of SVD and associated singular vectors within the ultrafast matrix formalism. We theoretically demonstrate that the separation of spatial and angular variables, rendered by SVD on ultrafast data, provides an elegant and straightforward way to optimize the angular coherence of backscattered data. In heterogeneous media, we demonstrate that the first spatial and angular singular vectors retrieve respectively the non-aberrated image of a region of interest, and the phase and amplitude of its aberration law. Numerical, in vitro and in vivo results prove the efficiency of the image correction, but also the accuracy of the aberrator determination. Based on spatial and angular coherence, we introduce a complete methodology for adaptive beamforming of ultrafast data, performed on successive isoplanatism patches undergoing SVD beamforming. The simplicity of this method paves the way to real-time adaptive ultrafast ultrasound imaging and provides a theoretical framework for future quantitative ultrasound applications.
doi:10.1109/tmi.2020.2986830 pmid:32286965 fatcat:i6thop2fyzeoxmta5qaqu4i3ta